Visual Pattern Mining
Abstract
Visual patterns, i.e., high-order combinations of visual words, have provided a discriminative abstraction of the high-dimensional bag-of-words image representation. However, the existing visual pattern mining schemes are built upon the ill-posed 2D photographic concurrences of visual words, rather than their real-world 3D concurrences, which incorrectly bind words from different objects/depth into an identical pattern to degenerate the mining precision. On the other hand, how to build a compact yet discriminative image representation from the mined patterns is left open, which is however highly demanded for many emerging applications like mobile visual search. In this paper, we propose a novel compact ...
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